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کامپیوتر و شبکه::
شباهت کسینوسی
Measuring distances between customers using cosine similarity, creating kNN graphs, calculating modularity, and clustering customers
The easiest way to explain cosine distance is to explain its opposite: cosine similarity.
Figure 2.41 An illustration of cosine similarity on two binary purchase vectors
You can say that they have a cosine similarity then of cos(45 degrees) = 0.707.
- cosine similarity can be used as a distance metric called cosine distance, which also ranges between 0 and 1.
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